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### Description As suggested by SciPy's doc, we will `Build against NumPy 2.0.0, then it will work for all NumPy versions with the same major version number (NumPy does maintain backwards ABI compatibility), and as far back as NumPy 1.19 series at the time of writing` I think it works because in [numpyconfig.h#L64](https://github.com/numpy/numpy/blob/main/numpy/_core/include/numpy/numpyconfig.h#L64) there is a macro NPY_FEATURE_VERSION. By default it is set to NPY_1_19_API_VERSION. And the NPY_FEATURE_VERSION macro controls ABI. This PR only upgrade the build time dependency; When a user installs ONNX Runtime, they still can use numpy 1.x. ### Motivation and Context Recently numpy published a new version, 2.0.0, which is incompatible with the latest ONNX Runtime release. |
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| .. | ||
| eager | ||
| post_to_dashboard | ||
| bundle_dlls_gpu.bat | ||
| bundle_nuget_with_native_headers.bat | ||
| extract_nuget_files.ps1 | ||
| extract_nuget_files_gpu.ps1 | ||
| extract_zip_files_gpu.ps1 | ||
| helpers.ps1 | ||
| install_third_party_deps.ps1 | ||
| jar_gpu_packaging.ps1 | ||
| jar_packaging.ps1 | ||
| post_binary_sizes_to_dashboard.py | ||
| post_code_coverage_to_dashboard.py | ||
| set_telemetry_var.ps1 | ||
| setup_env.bat | ||
| setup_env_cuda.bat | ||
| setup_env_gpu.bat | ||
| setup_env_trt.bat | ||
| setup_env_x86.bat | ||